{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f3375595-19d6-41ca-9f55-789acd07364b",
   "metadata": {},
   "source": [
    "# Create classification map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a88b3075-a676-4871-9c25-947c2193aedc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import eemont\n",
    "import geopandas\n",
    "import fiona\n",
    "import multiprocessing\n",
    "import geemap\n",
    "import pprint\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt\n",
    "import geemap.colormaps as cm\n",
    "import rioxarray\n",
    "import xarray\n",
    "\n",
    "from glob import glob\n",
    "import xarray as xr\n",
    "\n",
    "from pickle import load\n",
    "\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a80279cd-c927-4f33-bb63-15f8cc8e94b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p>To authorize access needed by Earth Engine, open the following\n",
       "        URL in a web browser and follow the instructions:</p>\n",
       "        <p><a href=https://code.earthengine.google.com/client-auth?scopes=https%3A//www.googleapis.com/auth/earthengine%20https%3A//www.googleapis.com/auth/devstorage.full_control&request_id=nP16vcGVWOl81Ziy7pqn2eT68bVGXpY7zwEFMsv6MMg&tc=wQD54WRKESnl5bISsC_v4vdqL9QKJL4QSDMGZQzrsXE&cc=Z5JDJRnqEQ7WD_mwB6cdRrEhLBmZ_Z0c8xWigrwNKyo>https://code.earthengine.google.com/client-auth?scopes=https%3A//www.googleapis.com/auth/earthengine%20https%3A//www.googleapis.com/auth/devstorage.full_control&request_id=nP16vcGVWOl81Ziy7pqn2eT68bVGXpY7zwEFMsv6MMg&tc=wQD54WRKESnl5bISsC_v4vdqL9QKJL4QSDMGZQzrsXE&cc=Z5JDJRnqEQ7WD_mwB6cdRrEhLBmZ_Z0c8xWigrwNKyo</a></p>\n",
       "        <p>The authorization workflow will generate a code, which you should paste in the box below.</p>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter verification code:  4/1AWtgzh4XGWRamQ6QFgOb98ZXIm4uZQue269t6_zhsiMatUMfBfMDZLlJE_g\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Successfully saved authorization token.\n"
     ]
    }
   ],
   "source": [
    "# authenticating\n",
    "ee.Authenticate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "265d77a3-0b44-4262-9fce-277ec78185e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initializing\n",
    "ee.Initialize()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25c061b0-ceb3-4d6c-8cac-2d400c1737c2",
   "metadata": {},
   "source": [
    "# Land layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 591,
   "id": "5d5ff502-8ba7-488e-bd2c-7eb7b799333d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "def paths_to_datetimeindex(paths, string_slice=(0, 10)):\n",
    "    try:\n",
    "        date_strings = [os.path.basename(i)[slice(*string_slice)] for i in paths]\n",
    "        return pd.to_datetime(date_strings)\n",
    "    except ValueError as e:\n",
    "        print(f\"Error: {e}. Please check your paths and string_slice inputs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 592,
   "id": "8c3d7cdf-1cc4-4ac2-bc5e-8004758a29c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['D:\\\\crop_season_stats\\\\images\\\\polder_37_4\\\\processing\\\\polder_37_4_stats_2016.tif',\n",
       " 'D:\\\\crop_season_stats\\\\images\\\\polder_37_4\\\\processing\\\\polder_37_4_stats_2017.tif',\n",
       " 'D:\\\\crop_season_stats\\\\images\\\\polder_37_4\\\\processing\\\\polder_37_4_stats_2018.tif',\n",
       " 'D:\\\\crop_season_stats\\\\images\\\\polder_37_4\\\\processing\\\\polder_37_4_stats_2019.tif',\n",
       " 'D:\\\\crop_season_stats\\\\images\\\\polder_37_4\\\\processing\\\\polder_37_4_stats_2020.tif',\n",
       " 'D:\\\\crop_season_stats\\\\images\\\\polder_37_4\\\\processing\\\\polder_37_4_stats_2021.tif']"
      ]
     },
     "execution_count": 592,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geotiff_list_polder  = glob(r'D:\\crop_season_stats\\images\\polder_37_4\\processing\\*')\n",
    "geotiff_list_polder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 593,
   "id": "971bb89d-3688-494c-825d-e1c1a4aa2bb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import itertools\n",
    "\n",
    "def paths_to_datetimeindex(paths, string_slice=(0, 10)):\n",
    "    if not isinstance(paths, list) or not paths:\n",
    "        raise ValueError(\"Input 'paths' must be a non-empty list of file paths.\")\n",
    "    date_strings = [os.path.basename(i)[slice(*string_slice)] for i in paths]\n",
    "    return pd.to_datetime(date_strings)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 594,
   "id": "183c06ed-4c66-4092-9353-d47ace92e3d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tedesco\\AppData\\Local\\Temp\\ipykernel_14072\\3608371674.py:6: DeprecationWarning: open_rasterio is Deprecated in favor of rioxarray. For information about transitioning, see: https://corteva.github.io/rioxarray/stable/getting_started/getting_started.html\n",
      "  geotiffs_da_polder = xr.concat([xr.open_rasterio(i) for i in geotiff_list_polder],\n"
     ]
    },
    {
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       "    doy_POS       (time, y, x) float64 273.0 273.0 273.0 ... 273.0 273.0 273.0\n",
       "    value_EOS     (time, y, x) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    doy_EOS       (time, y, x) float64 335.0 335.0 335.0 ... 335.0 335.0 335.0\n",
       "    Increase      (time, y, x) float64 60.0 60.0 60.0 60.0 ... 60.0 60.0 60.0\n",
       "    Decrease      (time, y, x) float64 62.0 62.0 62.0 62.0 ... 62.0 62.0 62.0\n",
       "    Total_Lenght  (time, y, x) float64 122.0 122.0 122.0 ... 122.0 122.0 122.0\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    crs:            +init=epsg:32645\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   (&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_E...\n",
       "    AREA_OR_POINT:  Area</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f491f2b7-989f-4888-9e05-24516635b31b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f491f2b7-989f-4888-9e05-24516635b31b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 6</li><li><span class='xr-has-index'>y</span>: 805</li><li><span class='xr-has-index'>x</span>: 1351</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-18d4c2e3-621a-4bf9-9b88-49c8b6e7c0a2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-18d4c2e3-621a-4bf9-9b88-49c8b6e7c0a2' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.509e+06 2.509e+06 ... 2.501e+06</div><input id='attrs-d0bcfc8e-1d83-407b-b643-e2083f496f94' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0bcfc8e-1d83-407b-b643-e2083f496f94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29cff308-b5ed-4e84-ae92-d8b072705bec' class='xr-var-data-in' type='checkbox'><label for='data-29cff308-b5ed-4e84-ae92-d8b072705bec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2509265., 2509255., 2509245., ..., 2501245., 2501235., 2501225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.869e+05 7.869e+05 ... 8.004e+05</div><input id='attrs-69dea717-93bb-45ea-9e09-40a2a3b8dd7b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-69dea717-93bb-45ea-9e09-40a2a3b8dd7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43aefaa3-a561-4764-bb4f-6c96a40b6ef5' class='xr-var-data-in' type='checkbox'><label for='data-43aefaa3-a561-4764-bb4f-6c96a40b6ef5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([786915., 786925., 786935., ..., 800395., 800405., 800415.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-01-01 ... 2021-01-01</div><input id='attrs-4ef437a6-fd9b-4ebd-9076-dd2158873228' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ef437a6-fd9b-4ebd-9076-dd2158873228' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49a29829-8b9b-4328-8e3e-a87bce2d85f4' class='xr-var-data-in' type='checkbox'><label for='data-49a29829-8b9b-4328-8e3e-a87bce2d85f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-01-01T00:00:00.000000000&#x27;, &#x27;2017-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-01-01T00:00:00.000000000&#x27;, &#x27;2019-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b4d9842e-f05c-45f3-a69c-4187a6cdf477' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b4d9842e-f05c-45f3-a69c-4187a6cdf477' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>value_SOS</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-447dfc4f-b6ed-4848-b331-4b4c6ee969b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-447dfc4f-b6ed-4848-b331-4b4c6ee969b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97bc3697-8c3b-45b8-b293-8af73f4e914c' class='xr-var-data-in' type='checkbox'><label for='data-97bc3697-8c3b-45b8-b293-8af73f4e914c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>doy_SOS</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>213.0 213.0 213.0 ... 213.0 213.0</div><input id='attrs-0f47b2ab-832e-40e3-bbff-6a0194a4f8a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f47b2ab-832e-40e3-bbff-6a0194a4f8a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8af7c758-8243-42ae-a950-39a36db26a32' class='xr-var-data-in' type='checkbox'><label for='data-8af7c758-8243-42ae-a950-39a36db26a32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        ...,\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.]],\n",
       "\n",
       "       [[213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        ...,\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.]],\n",
       "\n",
       "       [[213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.]],\n",
       "\n",
       "       [[213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        ...,\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.]],\n",
       "\n",
       "       [[213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        ...,\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.],\n",
       "        [213., 213., 213., ..., 213., 213., 213.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>value_POS</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-faf185ac-0664-4639-8f07-4c30cdf4f5c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-faf185ac-0664-4639-8f07-4c30cdf4f5c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6da36092-f4e5-47f5-9ac2-351d69c4d50f' class='xr-var-data-in' type='checkbox'><label for='data-6da36092-f4e5-47f5-9ac2-351d69c4d50f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>doy_POS</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>273.0 273.0 273.0 ... 273.0 273.0</div><input id='attrs-24cdce5e-1507-40c8-a271-17d4e1e1cee2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24cdce5e-1507-40c8-a271-17d4e1e1cee2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-deaa1314-d060-451a-a225-0dbdca5ef88f' class='xr-var-data-in' type='checkbox'><label for='data-deaa1314-d060-451a-a225-0dbdca5ef88f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        ...,\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.]],\n",
       "\n",
       "       [[273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        ...,\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.]],\n",
       "\n",
       "       [[273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.]],\n",
       "\n",
       "       [[273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        ...,\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.]],\n",
       "\n",
       "       [[273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        ...,\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.],\n",
       "        [273., 273., 273., ..., 273., 273., 273.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>value_EOS</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-16febbb3-fad8-4889-8a81-87be4aa7bc3f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-16febbb3-fad8-4889-8a81-87be4aa7bc3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13564198-cd32-46b5-8f7e-a7f150ecba1f' class='xr-var-data-in' type='checkbox'><label for='data-13564198-cd32-46b5-8f7e-a7f150ecba1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>doy_EOS</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>335.0 335.0 335.0 ... 335.0 335.0</div><input id='attrs-aa6de783-9964-4e2f-9c97-3c0eb3b596da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aa6de783-9964-4e2f-9c97-3c0eb3b596da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f65b8fb6-5bbc-4366-8768-58db629257a7' class='xr-var-data-in' type='checkbox'><label for='data-f65b8fb6-5bbc-4366-8768-58db629257a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        ...,\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.]],\n",
       "\n",
       "       [[335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        ...,\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.]],\n",
       "\n",
       "       [[335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.]],\n",
       "\n",
       "       [[335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        ...,\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.]],\n",
       "\n",
       "       [[335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        ...,\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.],\n",
       "        [335., 335., 335., ..., 335., 335., 335.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Increase</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>60.0 60.0 60.0 ... 60.0 60.0 60.0</div><input id='attrs-5c12e51e-a994-4546-8fef-3b78afe7eac5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5c12e51e-a994-4546-8fef-3b78afe7eac5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-990ec54d-aeac-4e9e-99a8-b1d3e0b35749' class='xr-var-data-in' type='checkbox'><label for='data-990ec54d-aeac-4e9e-99a8-b1d3e0b35749' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        ...,\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.]],\n",
       "\n",
       "       [[60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        ...,\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.]],\n",
       "\n",
       "       [[60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.]],\n",
       "\n",
       "       [[60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        ...,\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.]],\n",
       "\n",
       "       [[60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        ...,\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.],\n",
       "        [60., 60., 60., ..., 60., 60., 60.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Decrease</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>62.0 62.0 62.0 ... 62.0 62.0 62.0</div><input id='attrs-e7dde70f-fd27-4999-a6c1-9695429c2425' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7dde70f-fd27-4999-a6c1-9695429c2425' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e578b7a-6c00-4a4f-97c9-359b2f7d46b6' class='xr-var-data-in' type='checkbox'><label for='data-5e578b7a-6c00-4a4f-97c9-359b2f7d46b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        ...,\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.]],\n",
       "\n",
       "       [[62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        ...,\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.]],\n",
       "\n",
       "       [[62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.]],\n",
       "\n",
       "       [[62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        ...,\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.]],\n",
       "\n",
       "       [[62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        ...,\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.],\n",
       "        [62., 62., 62., ..., 62., 62., 62.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Total_Lenght</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>122.0 122.0 122.0 ... 122.0 122.0</div><input id='attrs-e7c83056-456b-4c7b-a58d-dfa609582b36' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7c83056-456b-4c7b-a58d-dfa609582b36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29d1ea01-ca38-486d-9d6d-6daec2f05f10' class='xr-var-data-in' type='checkbox'><label for='data-29d1ea01-ca38-486d-9d6d-6daec2f05f10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]],\n",
       "\n",
       "       [[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]],\n",
       "\n",
       "       [[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]],\n",
       "\n",
       "       [[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]],\n",
       "\n",
       "       [[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-46971411-1ab4-421d-ad33-767a464a933e' class='xr-section-summary-in' type='checkbox'  ><label for='section-46971411-1ab4-421d-ad33-767a464a933e' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f0e684b0-78f7-4f1c-9009-eddc342e6612' class='xr-index-data-in' type='checkbox'/><label for='index-f0e684b0-78f7-4f1c-9009-eddc342e6612' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([2509265.0, 2509255.0, 2509245.0, 2509235.0, 2509225.0, 2509215.0,\n",
       "              2509205.0, 2509195.0, 2509185.0, 2509175.0,\n",
       "              ...\n",
       "              2501315.0, 2501305.0, 2501295.0, 2501285.0, 2501275.0, 2501265.0,\n",
       "              2501255.0, 2501245.0, 2501235.0, 2501225.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=805))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a370acb1-4cc9-4371-bc3f-9c9e729ce60b' class='xr-index-data-in' type='checkbox'/><label for='index-a370acb1-4cc9-4371-bc3f-9c9e729ce60b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([786915.0, 786925.0, 786935.0, 786945.0, 786955.0, 786965.0,\n",
       "              786975.0, 786985.0, 786995.0, 787005.0,\n",
       "              ...\n",
       "              800325.0, 800335.0, 800345.0, 800355.0, 800365.0, 800375.0,\n",
       "              800385.0, 800395.0, 800405.0, 800415.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1351))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d8e62386-ef7d-4f1e-a97b-c7efe0219c42' class='xr-index-data-in' type='checkbox'/><label for='index-d8e62386-ef7d-4f1e-a97b-c7efe0219c42' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2016-01-01&#x27;, &#x27;2017-01-01&#x27;, &#x27;2018-01-01&#x27;, &#x27;2019-01-01&#x27;,\n",
       "               &#x27;2020-01-01&#x27;, &#x27;2021-01-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4594cec6-75fb-47da-b3af-a6791bf9523a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4594cec6-75fb-47da-b3af-a6791bf9523a' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)</dd><dt><span>crs :</span></dt><dd>+init=epsg:32645</dd><dt><span>res :</span></dt><dd>(10.0, 10.0)</dd><dt><span>is_tiled :</span></dt><dd>0</dd><dt><span>nodatavals :</span></dt><dd>(nan, nan, nan, nan, nan, nan, nan, nan, nan)</dd><dt><span>scales :</span></dt><dd>(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)</dd><dt><span>offsets :</span></dt><dd>(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)</dd><dt><span>descriptions :</span></dt><dd>(&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_EOS&#x27;, &#x27;doy_EOS&#x27;, &#x27;Increase&#x27;, &#x27;Decrease&#x27;, &#x27;Total_Lenght&#x27;)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (time: 6, y: 805, x: 1351)\n",
       "Coordinates:\n",
       "  * y             (y) float64 2.509e+06 2.509e+06 ... 2.501e+06 2.501e+06\n",
       "  * x             (x) float64 7.869e+05 7.869e+05 ... 8.004e+05 8.004e+05\n",
       "  * time          (time) datetime64[ns] 2016-01-01 2017-01-01 ... 2021-01-01\n",
       "Data variables:\n",
       "    value_SOS     (time, y, x) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    doy_SOS       (time, y, x) float64 213.0 213.0 213.0 ... 213.0 213.0 213.0\n",
       "    value_POS     (time, y, x) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    doy_POS       (time, y, x) float64 273.0 273.0 273.0 ... 273.0 273.0 273.0\n",
       "    value_EOS     (time, y, x) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    doy_EOS       (time, y, x) float64 335.0 335.0 335.0 ... 335.0 335.0 335.0\n",
       "    Increase      (time, y, x) float64 60.0 60.0 60.0 60.0 ... 60.0 60.0 60.0\n",
       "    Decrease      (time, y, x) float64 62.0 62.0 62.0 62.0 ... 62.0 62.0 62.0\n",
       "    Total_Lenght  (time, y, x) float64 122.0 122.0 122.0 ... 122.0 122.0 122.0\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    crs:            +init=epsg:32645\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   ('Value_SOS', 'doy_SOS', 'value_POS', 'doy_POS', 'value_E...\n",
       "    AREA_OR_POINT:  Area"
      ]
     },
     "execution_count": 594,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create variable used for time axis\n",
    "time_var_polder = xr.Variable('time', paths_to_datetimeindex(geotiff_list_polder,\n",
    "                                                      string_slice=(18, -4)))\n",
    "\n",
    "# Load in and concatenate all individual GeoTIFFs\n",
    "geotiffs_da_polder = xr.concat([xr.open_rasterio(i) for i in geotiff_list_polder],\n",
    "                        dim=time_var_polder)\n",
    "\n",
    "# Covert our xarray.DataArray into a xarray.Dataset\n",
    "geotiffs_ds_polder = geotiffs_da_polder.to_dataset('band')\n",
    "\n",
    "# Rename the variable to a more useful name\n",
    "geotiffs_ds_polder = geotiffs_ds_polder.rename({1:'value_SOS',\n",
    "                                                2:'doy_SOS',\n",
    "                                                3:'value_POS',\n",
    "                                                4:'doy_POS',\n",
    "                                                5:'value_EOS',\n",
    "                                                6:'doy_EOS',\n",
    "                                                7:'Increase',\n",
    "                                                8:'Decrease',\n",
    "                                                9:'Total_Lenght'\n",
    "                                           \n",
    "                                           })\n",
    "# Print the output\n",
    "geotiffs_ds_polder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 595,
   "id": "ecc0ad97-6547-4936-bb93-8ca7f3bbc0a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
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       "\n",
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       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
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       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       "dl.xr-attrs {\n",
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       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (time: 6, y: 805, x: 1351)\n",
       "Coordinates:\n",
       "  * y             (y) float64 2.509e+06 2.509e+06 ... 2.501e+06 2.501e+06\n",
       "  * x             (x) float64 7.869e+05 7.869e+05 ... 8.004e+05 8.004e+05\n",
       "  * time          (time) datetime64[ns] 2016-01-01 2017-01-01 ... 2021-01-01\n",
       "Data variables:\n",
       "    Total_Lenght  (time, y, x) float64 122.0 122.0 122.0 ... 122.0 122.0 122.0\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    crs:            +init=epsg:32645\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   (&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_E...\n",
       "    AREA_OR_POINT:  Area</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-bbd08e77-dc49-42b3-84e4-afbc59396ebc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bbd08e77-dc49-42b3-84e4-afbc59396ebc' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 6</li><li><span class='xr-has-index'>y</span>: 805</li><li><span class='xr-has-index'>x</span>: 1351</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b8153a75-f9a0-4624-a614-923b9441ec5e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b8153a75-f9a0-4624-a614-923b9441ec5e' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.509e+06 2.509e+06 ... 2.501e+06</div><input id='attrs-2102b93d-c886-46d7-be57-642da2b9e885' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2102b93d-c886-46d7-be57-642da2b9e885' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21c65abf-48a4-41c0-805d-1f61e485abbe' class='xr-var-data-in' type='checkbox'><label for='data-21c65abf-48a4-41c0-805d-1f61e485abbe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2509265., 2509255., 2509245., ..., 2501245., 2501235., 2501225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.869e+05 7.869e+05 ... 8.004e+05</div><input id='attrs-0645c254-d2d5-4add-8b8a-64db939eb668' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0645c254-d2d5-4add-8b8a-64db939eb668' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68d76b31-5b32-4a49-9303-3741684ece11' class='xr-var-data-in' type='checkbox'><label for='data-68d76b31-5b32-4a49-9303-3741684ece11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([786915., 786925., 786935., ..., 800395., 800405., 800415.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-01-01 ... 2021-01-01</div><input id='attrs-a2b00d4f-5505-4435-a5fd-fcae6a7295b6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2b00d4f-5505-4435-a5fd-fcae6a7295b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3d196cb-fe66-4acb-9706-b9efdfb2dbe6' class='xr-var-data-in' type='checkbox'><label for='data-c3d196cb-fe66-4acb-9706-b9efdfb2dbe6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-01-01T00:00:00.000000000&#x27;, &#x27;2017-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-01-01T00:00:00.000000000&#x27;, &#x27;2019-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9ef9ad77-d5bb-47bd-967c-02d71393d8d7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9ef9ad77-d5bb-47bd-967c-02d71393d8d7' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Total_Lenght</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>122.0 122.0 122.0 ... 122.0 122.0</div><input id='attrs-b29a415a-4b5c-42ee-a23a-a0c3369bd8a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b29a415a-4b5c-42ee-a23a-a0c3369bd8a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13ca8290-6067-4aed-a5c2-5e1d02fc7c55' class='xr-var-data-in' type='checkbox'><label for='data-13ca8290-6067-4aed-a5c2-5e1d02fc7c55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]],\n",
       "\n",
       "       [[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]],\n",
       "\n",
       "       [[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]],\n",
       "\n",
       "       [[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]],\n",
       "\n",
       "       [[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-62df4e04-69b7-4af9-8e9b-54ef5cb11cf5' class='xr-section-summary-in' type='checkbox'  ><label for='section-62df4e04-69b7-4af9-8e9b-54ef5cb11cf5' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a0fdf9c4-73d2-43e2-bb3c-1f6c88e3dd50' class='xr-index-data-in' type='checkbox'/><label for='index-a0fdf9c4-73d2-43e2-bb3c-1f6c88e3dd50' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([2509265.0, 2509255.0, 2509245.0, 2509235.0, 2509225.0, 2509215.0,\n",
       "              2509205.0, 2509195.0, 2509185.0, 2509175.0,\n",
       "              ...\n",
       "              2501315.0, 2501305.0, 2501295.0, 2501285.0, 2501275.0, 2501265.0,\n",
       "              2501255.0, 2501245.0, 2501235.0, 2501225.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=805))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9aad12e7-ef5c-4cf5-afe3-f92da3fdb4d5' class='xr-index-data-in' type='checkbox'/><label for='index-9aad12e7-ef5c-4cf5-afe3-f92da3fdb4d5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([786915.0, 786925.0, 786935.0, 786945.0, 786955.0, 786965.0,\n",
       "              786975.0, 786985.0, 786995.0, 787005.0,\n",
       "              ...\n",
       "              800325.0, 800335.0, 800345.0, 800355.0, 800365.0, 800375.0,\n",
       "              800385.0, 800395.0, 800405.0, 800415.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1351))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-619ee04e-8ca1-4b02-80f4-22b8ac539d66' class='xr-index-data-in' type='checkbox'/><label for='index-619ee04e-8ca1-4b02-80f4-22b8ac539d66' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2016-01-01&#x27;, &#x27;2017-01-01&#x27;, &#x27;2018-01-01&#x27;, &#x27;2019-01-01&#x27;,\n",
       "               &#x27;2020-01-01&#x27;, &#x27;2021-01-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a64449e0-4b0e-4032-849a-7a92894b5d0d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a64449e0-4b0e-4032-849a-7a92894b5d0d' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)</dd><dt><span>crs :</span></dt><dd>+init=epsg:32645</dd><dt><span>res :</span></dt><dd>(10.0, 10.0)</dd><dt><span>is_tiled :</span></dt><dd>0</dd><dt><span>nodatavals :</span></dt><dd>(nan, nan, nan, nan, nan, nan, nan, nan, nan)</dd><dt><span>scales :</span></dt><dd>(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)</dd><dt><span>offsets :</span></dt><dd>(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)</dd><dt><span>descriptions :</span></dt><dd>(&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_EOS&#x27;, &#x27;doy_EOS&#x27;, &#x27;Increase&#x27;, &#x27;Decrease&#x27;, &#x27;Total_Lenght&#x27;)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (time: 6, y: 805, x: 1351)\n",
       "Coordinates:\n",
       "  * y             (y) float64 2.509e+06 2.509e+06 ... 2.501e+06 2.501e+06\n",
       "  * x             (x) float64 7.869e+05 7.869e+05 ... 8.004e+05 8.004e+05\n",
       "  * time          (time) datetime64[ns] 2016-01-01 2017-01-01 ... 2021-01-01\n",
       "Data variables:\n",
       "    Total_Lenght  (time, y, x) float64 122.0 122.0 122.0 ... 122.0 122.0 122.0\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    crs:            +init=epsg:32645\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   ('Value_SOS', 'doy_SOS', 'value_POS', 'doy_POS', 'value_E...\n",
       "    AREA_OR_POINT:  Area"
      ]
     },
     "execution_count": 595,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select variables\n",
    "variable_peak = ['Total_Lenght']\n",
    "\n",
    "#variable_peak = ['v_pos','doy_pos']\n",
    "\n",
    "\n",
    "polder_maps = geotiffs_ds_polder[variable_peak]\n",
    "polder_maps"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e163d911-827f-4f53-904f-3019b331a002",
   "metadata": {},
   "source": [
    "# Layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 596,
   "id": "ef859bbd-8c0d-4d78-9686-860650c4a46b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "# importing field boundary\n",
    "fieldbound_orginal = geemap.shp_to_ee(r'D:\\crop_season_stats\\shapefile\\polder_37\\polder_37_4.shp', crs='epsg:32645')\n",
    "field_centroid = gpd.read_file(r'D:\\crop_season_stats\\shapefile\\polder_37\\polder_37_4.shp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 597,
   "id": "88eb4f2b-5d6d-4ccb-baae-6437d5d7692a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8068.336744690244"
      ]
     },
     "execution_count": 597,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking area, in hectares\n",
    "AOI = fieldbound_orginal\n",
    "fieldbound_orginal.geometry().area(maxError=2).divide(100 * 100).getInfo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 598,
   "id": "541ab326-59f7-4bf5-bcad-4337758562aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "esa = ee.ImageCollection(\"ESA/WorldCover/v200\")\n",
    "\n",
    "water = ee.Image(\"JRC/GSW1_4/GlobalSurfaceWater\")\n",
    "water_transic = water.select('transition')\n",
    "water_transic = water_transic.set(\"system:time_start\", ee.Date(\"2020-12-31T23:00:00\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 599,
   "id": "a69834a8-2296-47b8-b9f7-c4fb09500acd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3145d35c75f84f5595e05ee39f942786",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Requesting data:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "997593218753457391ad6be6de0bde2c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading data:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "10198c055fd54452a9d04c1cf6c8a07a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading:   0%|          | 0.00/37.5k [00:00<?, ?iB/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 578 ms\n",
      "Wall time: 5.89 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "import wxee\n",
    "esa_xarray = esa.wx.to_xarray(scale = 10, crs = \"EPSG:32645\", region=AOI.geometry())\n",
    "water_xarray = water_transic.wx.to_xarray(scale = 10, crs = \"EPSG:32645\", region=AOI.geometry())\n",
    "water_xarray = water_xarray.rename({'transition':'Map'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 600,
   "id": "fb52bb0e-5394-41ef-981b-954b3f8b7f12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x21629d789d0>"
      ]
     },
     "execution_count": 600,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lands_ = esa_xarray.where((esa_xarray == 10) | (esa_xarray == 30) \\\n",
    "                          | (esa_xarray == 50) | (esa_xarray == 60)\\\n",
    "                          | (esa_xarray == 90))\n",
    "\n",
    "mask_others = 1 * np.ones((lands_.dims['y'], lands_.dims['x'])) * np.isnan(lands_.Map.isel(time=0))\n",
    "mask_others.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 601,
   "id": "49b22804-f629-4931-a86b-a8964757823b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2167a81c310>"
      ]
     },
     "execution_count": 601,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#water_ = water_xarray.where( (water_xarray == 1) | (water_xarray == 2))\n",
    "water_ = water_xarray.where(water_xarray == 1)\n",
    "mask_water = 1 * np.ones((water_.dims['y'], water_.dims['x'])) * np.isnan(water_.Map.isel(time=0))\n",
    "mask_water.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 602,
   "id": "c55fb844-235e-4bf0-9bb4-a233ca55cd78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2167eb82640>"
      ]
     },
     "execution_count": 602,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask_combine = xarray.Dataset({'Map': mask_others + mask_water})\n",
    "mask_combine = mask_combine.where(mask_combine['Map'] == 1, drop=True)\n",
    "\n",
    "# set CRS for the output file\n",
    "mask_combine.rio.write_crs(\"EPSG:32645\", inplace=True)\n",
    "\n",
    "# set CRS for field centroid\n",
    "field_centroid_utm = field_centroid.to_crs(epsg=32645)\n",
    "\n",
    "# create the clip mask\n",
    "mask_class = mask_combine.Map.where(~np.isnan(mask_combine.Map), 0)\n",
    "\n",
    "# clip the data using the field centroid shape\n",
    "mask_class = mask_class.rio.clip(field_centroid_utm.geometry.values)\n",
    "\n",
    "# view the clipped data\n",
    "mask_class.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf0b5d8c-8022-470e-bcbb-3ccec7804998",
   "metadata": {},
   "source": [
    "# Separate data by year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 603,
   "id": "562ea520-cef7-41a8-8fc1-fb209210102d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
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       "</svg>\n",
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       "\n",
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       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
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       "\n",
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       "  display: block !important;\n",
       "  min-width: 300px;\n",
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       "\n",
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       "\n",
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       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
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       "\n",
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       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
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       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (time: 1, y: 805, x: 1351)\n",
       "Coordinates:\n",
       "  * y             (y) float64 2.509e+06 2.509e+06 ... 2.501e+06 2.501e+06\n",
       "  * x             (x) float64 7.869e+05 7.869e+05 ... 8.004e+05 8.004e+05\n",
       "  * time          (time) datetime64[ns] 2021-01-01\n",
       "Data variables:\n",
       "    Total_Lenght  (time, y, x) float64 122.0 122.0 122.0 ... 122.0 122.0 122.0\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    crs:            +init=epsg:32645\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   (&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_E...\n",
       "    AREA_OR_POINT:  Area</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1a38838d-2739-419e-8716-c0e635a51e5a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1a38838d-2739-419e-8716-c0e635a51e5a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>y</span>: 805</li><li><span class='xr-has-index'>x</span>: 1351</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-87cf8b57-dd3d-4331-a298-bec724e1e791' class='xr-section-summary-in' type='checkbox'  checked><label for='section-87cf8b57-dd3d-4331-a298-bec724e1e791' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.509e+06 2.509e+06 ... 2.501e+06</div><input id='attrs-e0d5795a-5d83-4835-aa14-2208122ddab8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0d5795a-5d83-4835-aa14-2208122ddab8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8abca375-4fa9-4548-b1b3-f02abadb732b' class='xr-var-data-in' type='checkbox'><label for='data-8abca375-4fa9-4548-b1b3-f02abadb732b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2509265., 2509255., 2509245., ..., 2501245., 2501235., 2501225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.869e+05 7.869e+05 ... 8.004e+05</div><input id='attrs-8f12199a-64b4-497f-9f20-8418e18a046c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f12199a-64b4-497f-9f20-8418e18a046c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3cacb39-028d-4d91-be3b-f5052b80c6ee' class='xr-var-data-in' type='checkbox'><label for='data-a3cacb39-028d-4d91-be3b-f5052b80c6ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([786915., 786925., 786935., ..., 800395., 800405., 800415.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01</div><input id='attrs-8d9e06f5-1651-444c-bc45-10076a3525ce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8d9e06f5-1651-444c-bc45-10076a3525ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab56b535-f0e1-4e8f-aea3-c1420fda7f80' class='xr-var-data-in' type='checkbox'><label for='data-ab56b535-f0e1-4e8f-aea3-c1420fda7f80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-968943cd-b409-4c63-9826-1c0c908ecc4f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-968943cd-b409-4c63-9826-1c0c908ecc4f' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Total_Lenght</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>122.0 122.0 122.0 ... 122.0 122.0</div><input id='attrs-6c7950e5-a9b3-446f-9097-acaefdfd91bb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c7950e5-a9b3-446f-9097-acaefdfd91bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cecbb51-9441-41e5-802c-e39ed08d760c' class='xr-var-data-in' type='checkbox'><label for='data-2cecbb51-9441-41e5-802c-e39ed08d760c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95ec0fd9-ec7d-4728-9aed-c151b36887d3' class='xr-section-summary-in' type='checkbox'  ><label for='section-95ec0fd9-ec7d-4728-9aed-c151b36887d3' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-12c87686-8e3e-40ac-9814-a7b967e8e047' class='xr-index-data-in' type='checkbox'/><label for='index-12c87686-8e3e-40ac-9814-a7b967e8e047' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([2509265.0, 2509255.0, 2509245.0, 2509235.0, 2509225.0, 2509215.0,\n",
       "              2509205.0, 2509195.0, 2509185.0, 2509175.0,\n",
       "              ...\n",
       "              2501315.0, 2501305.0, 2501295.0, 2501285.0, 2501275.0, 2501265.0,\n",
       "              2501255.0, 2501245.0, 2501235.0, 2501225.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=805))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4c954956-9ea5-43e0-a95e-4c2b4161c7ed' class='xr-index-data-in' type='checkbox'/><label for='index-4c954956-9ea5-43e0-a95e-4c2b4161c7ed' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([786915.0, 786925.0, 786935.0, 786945.0, 786955.0, 786965.0,\n",
       "              786975.0, 786985.0, 786995.0, 787005.0,\n",
       "              ...\n",
       "              800325.0, 800335.0, 800345.0, 800355.0, 800365.0, 800375.0,\n",
       "              800385.0, 800395.0, 800405.0, 800415.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1351))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ebcc9371-f201-4381-9ae8-81f04da8425b' class='xr-index-data-in' type='checkbox'/><label for='index-ebcc9371-f201-4381-9ae8-81f04da8425b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-01-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2c36205d-a6b4-4360-af60-ad7e266b94e3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2c36205d-a6b4-4360-af60-ad7e266b94e3' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)</dd><dt><span>crs :</span></dt><dd>+init=epsg:32645</dd><dt><span>res :</span></dt><dd>(10.0, 10.0)</dd><dt><span>is_tiled :</span></dt><dd>0</dd><dt><span>nodatavals :</span></dt><dd>(nan, nan, nan, nan, nan, nan, nan, nan, nan)</dd><dt><span>scales :</span></dt><dd>(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)</dd><dt><span>offsets :</span></dt><dd>(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)</dd><dt><span>descriptions :</span></dt><dd>(&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_EOS&#x27;, &#x27;doy_EOS&#x27;, &#x27;Increase&#x27;, &#x27;Decrease&#x27;, &#x27;Total_Lenght&#x27;)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (time: 1, y: 805, x: 1351)\n",
       "Coordinates:\n",
       "  * y             (y) float64 2.509e+06 2.509e+06 ... 2.501e+06 2.501e+06\n",
       "  * x             (x) float64 7.869e+05 7.869e+05 ... 8.004e+05 8.004e+05\n",
       "  * time          (time) datetime64[ns] 2021-01-01\n",
       "Data variables:\n",
       "    Total_Lenght  (time, y, x) float64 122.0 122.0 122.0 ... 122.0 122.0 122.0\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    crs:            +init=epsg:32645\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   ('Value_SOS', 'doy_SOS', 'value_POS', 'doy_POS', 'value_E...\n",
       "    AREA_OR_POINT:  Area"
      ]
     },
     "execution_count": 603,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create data by year\n",
    "polder_maps_2016 = polder_maps.sel(time='2016')\n",
    "polder_maps_2017 = polder_maps.sel(time='2017')\n",
    "polder_maps_2018 = polder_maps.sel(time='2018')\n",
    "polder_maps_2019 = polder_maps.sel(time='2019')\n",
    "polder_maps_2020 = polder_maps.sel(time='2020')\n",
    "polder_maps_2021 = polder_maps.sel(time='2021')\n",
    "polder_maps_2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 604,
   "id": "aa5fc3d3-b48f-4662-9d38-e75b702916f3",
   "metadata": {},
   "outputs": [
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       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   (&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_E...\n",
       "    AREA_OR_POINT:  Area</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-dfb155b5-edce-48ac-9f6d-dd1c4631c80b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dfb155b5-edce-48ac-9f6d-dd1c4631c80b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>y</span>: 805</li><li><span class='xr-has-index'>x</span>: 1351</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9943ff92-ac57-4f84-8e3c-3c857df61017' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9943ff92-ac57-4f84-8e3c-3c857df61017' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.509e+06 2.509e+06 ... 2.501e+06</div><input id='attrs-126aad98-155b-4085-9919-615c057b8f6d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-126aad98-155b-4085-9919-615c057b8f6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-405468b0-5962-4522-91bd-77e0a9429648' class='xr-var-data-in' type='checkbox'><label for='data-405468b0-5962-4522-91bd-77e0a9429648' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2509265., 2509255., 2509245., ..., 2501245., 2501235., 2501225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.869e+05 7.869e+05 ... 8.004e+05</div><input id='attrs-efdf738e-398a-465d-8d57-44f736049a8e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-efdf738e-398a-465d-8d57-44f736049a8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e094a984-06b0-48d0-b3e0-873dae71ca95' class='xr-var-data-in' type='checkbox'><label for='data-e094a984-06b0-48d0-b3e0-873dae71ca95' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([786915., 786925., 786935., ..., 800395., 800405., 800415.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01</div><input id='attrs-87ab12a0-c78a-4d7b-9233-a4a17c4f9cd4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-87ab12a0-c78a-4d7b-9233-a4a17c4f9cd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-449af12a-f8fc-48ef-b174-2810044baff5' class='xr-var-data-in' type='checkbox'><label for='data-449af12a-f8fc-48ef-b174-2810044baff5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-af900e50-fd65-46c2-a31a-114544c7ad1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af900e50-fd65-46c2-a31a-114544c7ad1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a68becc-6724-4783-8a5e-7b8652b68869' class='xr-var-data-in' type='checkbox'><label for='data-5a68becc-6724-4783-8a5e-7b8652b68869' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 45N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,87],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32645&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 45N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>87.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 45N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,87],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32645&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>786910.0 10.0 0.0 2509270.0 0.0 -10.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-40b8bef2-5eef-4405-acc0-d84b7b785696' class='xr-section-summary-in' type='checkbox'  checked><label for='section-40b8bef2-5eef-4405-acc0-d84b7b785696' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Total_Lenght</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>122.0 122.0 122.0 ... 122.0 122.0</div><input id='attrs-74ba4f67-5531-4a4d-9dd0-b2a7f351e95b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74ba4f67-5531-4a4d-9dd0-b2a7f351e95b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7255f3d2-27fa-44d0-82ee-caf9c48ac51f' class='xr-var-data-in' type='checkbox'><label for='data-7255f3d2-27fa-44d0-82ee-caf9c48ac51f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        ...,\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.],\n",
       "        [122., 122., 122., ..., 122., 122., 122.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-15241c9b-c11b-4755-b0b1-c4f9fcad73e7' class='xr-section-summary-in' type='checkbox'  ><label for='section-15241c9b-c11b-4755-b0b1-c4f9fcad73e7' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b0373179-0bbb-4901-a28b-1c0105a8d171' class='xr-index-data-in' type='checkbox'/><label for='index-b0373179-0bbb-4901-a28b-1c0105a8d171' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([2509265.0, 2509255.0, 2509245.0, 2509235.0, 2509225.0, 2509215.0,\n",
       "              2509205.0, 2509195.0, 2509185.0, 2509175.0,\n",
       "              ...\n",
       "              2501315.0, 2501305.0, 2501295.0, 2501285.0, 2501275.0, 2501265.0,\n",
       "              2501255.0, 2501245.0, 2501235.0, 2501225.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=805))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bf6c6286-8930-490f-9277-7381cdc354b6' class='xr-index-data-in' type='checkbox'/><label for='index-bf6c6286-8930-490f-9277-7381cdc354b6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([786915.0, 786925.0, 786935.0, 786945.0, 786955.0, 786965.0,\n",
       "              786975.0, 786985.0, 786995.0, 787005.0,\n",
       "              ...\n",
       "              800325.0, 800335.0, 800345.0, 800355.0, 800365.0, 800375.0,\n",
       "              800385.0, 800395.0, 800405.0, 800415.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1351))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cad76076-5e09-44a8-9d34-1fca94d2017c' class='xr-index-data-in' type='checkbox'/><label for='index-cad76076-5e09-44a8-9d34-1fca94d2017c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-01-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-529b952c-6d79-460e-ac60-a4efef9e1f46' class='xr-section-summary-in' type='checkbox'  checked><label for='section-529b952c-6d79-460e-ac60-a4efef9e1f46' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)</dd><dt><span>res :</span></dt><dd>(10.0, 10.0)</dd><dt><span>is_tiled :</span></dt><dd>0</dd><dt><span>nodatavals :</span></dt><dd>(nan, nan, nan, nan, nan, nan, nan, nan, nan)</dd><dt><span>scales :</span></dt><dd>(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)</dd><dt><span>offsets :</span></dt><dd>(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)</dd><dt><span>descriptions :</span></dt><dd>(&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_EOS&#x27;, &#x27;doy_EOS&#x27;, &#x27;Increase&#x27;, &#x27;Decrease&#x27;, &#x27;Total_Lenght&#x27;)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (time: 1, y: 805, x: 1351)\n",
       "Coordinates:\n",
       "  * y             (y) float64 2.509e+06 2.509e+06 ... 2.501e+06 2.501e+06\n",
       "  * x             (x) float64 7.869e+05 7.869e+05 ... 8.004e+05 8.004e+05\n",
       "  * time          (time) datetime64[ns] 2021-01-01\n",
       "    spatial_ref   int32 0\n",
       "Data variables:\n",
       "    Total_Lenght  (time, y, x) float64 122.0 122.0 122.0 ... 122.0 122.0 122.0\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   ('Value_SOS', 'doy_SOS', 'value_POS', 'doy_POS', 'value_E...\n",
       "    AREA_OR_POINT:  Area"
      ]
     },
     "execution_count": 604,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import rioxarray\n",
    "polder_maps_2016.rio.write_crs(\"EPSG:32645\", inplace=True)\n",
    "polder_maps_2017.rio.write_crs(\"EPSG:32645\", inplace=True)\n",
    "polder_maps_2018.rio.write_crs(\"EPSG:32645\", inplace=True)\n",
    "polder_maps_2019.rio.write_crs(\"EPSG:32645\", inplace=True)\n",
    "polder_maps_2020.rio.write_crs(\"EPSG:32645\", inplace=True)\n",
    "polder_maps_2021.rio.write_crs(\"EPSG:32645\", inplace=True)\n",
    "#polder_class_clipped.rio.write_crs(\"EPSG:32645\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 605,
   "id": "36538efa-ea89-42fd-8c14-b27faaaca4c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2168b291c70>"
      ]
     },
     "execution_count": 605,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class_polder_class_16 =  polder_maps_2016.where(mask_class ==0)\n",
    "class_polder_class_17 =  polder_maps_2017.where(mask_class ==0)\n",
    "class_polder_class_18 =  polder_maps_2018.where(mask_class ==0)\n",
    "class_polder_class_19 =  polder_maps_2019.where(mask_class ==0)\n",
    "class_polder_class_20 =  polder_maps_2020.where(mask_class ==0)\n",
    "class_polder_class_21 =  polder_maps_2021.where(mask_class ==0)\n",
    "\n",
    "class_polder_class_21.Total_Lenght.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6654258e-7bfd-4d1c-906f-d6b5fc164566",
   "metadata": {},
   "source": [
    "# Scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 606,
   "id": "c8f65a2e-e720-479d-9b98-ba52baf0f379",
   "metadata": {},
   "outputs": [],
   "source": [
    "import joblib\n",
    "from joblib import load, dump\n",
    "from xarray import DataArray\n",
    "\n",
    "scaler = joblib.load(r'D:\\crop_season_stats\\results\\model\\scaler_data_los.pkl')\n",
    "\n",
    "def scale_xarray(da: DataArray):\n",
    "    scaled_values = scaler.transform(da.values.reshape(-1, 1))\n",
    "    return DataArray(scaled_values.reshape(*da.shape), coords=da.coords, dims=da.dims)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 607,
   "id": "61544c8f-ded3-4e05-bf84-ab3716af12b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([128.24043716]), array([23.23577428]), StandardScaler())"
      ]
     },
     "execution_count": 607,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaler.mean_,scaler.scale_,scaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 608,
   "id": "4f8a0b66-03d2-4138-bb57-9eb41558a977",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tedesco\\Anaconda3\\envs\\tedesco\\lib\\site-packages\\sklearn\\base.py:409: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\tedesco\\Anaconda3\\envs\\tedesco\\lib\\site-packages\\sklearn\\base.py:409: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\tedesco\\Anaconda3\\envs\\tedesco\\lib\\site-packages\\sklearn\\base.py:409: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\tedesco\\Anaconda3\\envs\\tedesco\\lib\\site-packages\\sklearn\\base.py:409: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\tedesco\\Anaconda3\\envs\\tedesco\\lib\\site-packages\\sklearn\\base.py:409: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\tedesco\\Anaconda3\\envs\\tedesco\\lib\\site-packages\\sklearn\\base.py:409: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "polder_maps_2016['Total_Lenght'] = scale_xarray(class_polder_class_16.Total_Lenght)\n",
    "polder_maps_2017['Total_Lenght'] = scale_xarray(class_polder_class_17.Total_Lenght)\n",
    "polder_maps_2018['Total_Lenght'] = scale_xarray(class_polder_class_18.Total_Lenght)\n",
    "polder_maps_2019['Total_Lenght'] = scale_xarray(class_polder_class_19.Total_Lenght)\n",
    "polder_maps_2020['Total_Lenght'] = scale_xarray(class_polder_class_20.Total_Lenght)\n",
    "polder_maps_2021['Total_Lenght'] = scale_xarray(class_polder_class_21.Total_Lenght)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 609,
   "id": "4fbaf3c3-e66b-473d-b245-a44cfb6e2ea5",
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (time: 1, y: 805, x: 1351)\n",
       "Coordinates:\n",
       "  * y             (y) float64 2.509e+06 2.509e+06 ... 2.501e+06 2.501e+06\n",
       "  * x             (x) float64 7.869e+05 7.869e+05 ... 8.004e+05 8.004e+05\n",
       "  * time          (time) datetime64[ns] 2020-01-01\n",
       "    spatial_ref   int32 0\n",
       "Data variables:\n",
       "    Total_Lenght  (time, y, x) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   (&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_E...\n",
       "    AREA_OR_POINT:  Area</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e6dd7508-27c0-44c9-aac9-ed5bcc7c8da8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e6dd7508-27c0-44c9-aac9-ed5bcc7c8da8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>y</span>: 805</li><li><span class='xr-has-index'>x</span>: 1351</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4113ee71-84c6-479d-a285-79a631c0e3cc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4113ee71-84c6-479d-a285-79a631c0e3cc' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.509e+06 2.509e+06 ... 2.501e+06</div><input id='attrs-79958726-5447-4fd0-a289-0c55777f59f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79958726-5447-4fd0-a289-0c55777f59f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4714f92c-cc13-4021-bc9a-fad321d3900f' class='xr-var-data-in' type='checkbox'><label for='data-4714f92c-cc13-4021-bc9a-fad321d3900f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2509265., 2509255., 2509245., ..., 2501245., 2501235., 2501225.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.869e+05 7.869e+05 ... 8.004e+05</div><input id='attrs-bbabaab7-9990-47ba-82a3-6afb58ccc52c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bbabaab7-9990-47ba-82a3-6afb58ccc52c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac154010-8b2b-4628-8166-630f9cd8112f' class='xr-var-data-in' type='checkbox'><label for='data-ac154010-8b2b-4628-8166-630f9cd8112f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([786915., 786925., 786935., ..., 800395., 800405., 800415.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-01-01</div><input id='attrs-09be5357-2715-4fea-9fc1-f735cf5a8721' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-09be5357-2715-4fea-9fc1-f735cf5a8721' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50d63207-12ef-45aa-b8e7-835ad4f75e46' class='xr-var-data-in' type='checkbox'><label for='data-50d63207-12ef-45aa-b8e7-835ad4f75e46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-bd5bc5e7-1e16-4b95-ac0c-66f02e37c2e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd5bc5e7-1e16-4b95-ac0c-66f02e37c2e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abbfac3a-d134-4d89-993c-11548db6778c' class='xr-var-data-in' type='checkbox'><label for='data-abbfac3a-d134-4d89-993c-11548db6778c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 45N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,87],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32645&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 45N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>87.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 45N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,87],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32645&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>786910.0 10.0 0.0 2509270.0 0.0 -10.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c7b387e-d68f-4ca3-863d-d09814eefcc8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7c7b387e-d68f-4ca3-863d-d09814eefcc8' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Total_Lenght</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b9f863db-2d20-422d-b429-4e2aa204c6b1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b9f863db-2d20-422d-b429-4e2aa204c6b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15bf3c3c-96f7-4df4-9623-a27b3760d200' class='xr-var-data-in' type='checkbox'><label for='data-15bf3c3c-96f7-4df4-9623-a27b3760d200' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2aad4870-ffd6-49f6-9c1c-be90d3fe5fd1' class='xr-section-summary-in' type='checkbox'  ><label for='section-2aad4870-ffd6-49f6-9c1c-be90d3fe5fd1' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8de45014-4fa1-4621-904b-55bdf8dfa216' class='xr-index-data-in' type='checkbox'/><label for='index-8de45014-4fa1-4621-904b-55bdf8dfa216' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([2509265.0, 2509255.0, 2509245.0, 2509235.0, 2509225.0, 2509215.0,\n",
       "              2509205.0, 2509195.0, 2509185.0, 2509175.0,\n",
       "              ...\n",
       "              2501315.0, 2501305.0, 2501295.0, 2501285.0, 2501275.0, 2501265.0,\n",
       "              2501255.0, 2501245.0, 2501235.0, 2501225.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=805))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-558cb0ee-ba2c-4fef-b6b5-5c9c885af9fc' class='xr-index-data-in' type='checkbox'/><label for='index-558cb0ee-ba2c-4fef-b6b5-5c9c885af9fc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([786915.0, 786925.0, 786935.0, 786945.0, 786955.0, 786965.0,\n",
       "              786975.0, 786985.0, 786995.0, 787005.0,\n",
       "              ...\n",
       "              800325.0, 800335.0, 800345.0, 800355.0, 800365.0, 800375.0,\n",
       "              800385.0, 800395.0, 800405.0, 800415.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1351))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ee7b8bf6-02fb-4078-98fd-2bb01f373ca0' class='xr-index-data-in' type='checkbox'/><label for='index-ee7b8bf6-02fb-4078-98fd-2bb01f373ca0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-01-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d70fae9c-365c-4258-8aa5-89910c94bc74' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d70fae9c-365c-4258-8aa5-89910c94bc74' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)</dd><dt><span>res :</span></dt><dd>(10.0, 10.0)</dd><dt><span>is_tiled :</span></dt><dd>0</dd><dt><span>nodatavals :</span></dt><dd>(nan, nan, nan, nan, nan, nan, nan, nan, nan)</dd><dt><span>scales :</span></dt><dd>(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)</dd><dt><span>offsets :</span></dt><dd>(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)</dd><dt><span>descriptions :</span></dt><dd>(&#x27;Value_SOS&#x27;, &#x27;doy_SOS&#x27;, &#x27;value_POS&#x27;, &#x27;doy_POS&#x27;, &#x27;value_EOS&#x27;, &#x27;doy_EOS&#x27;, &#x27;Increase&#x27;, &#x27;Decrease&#x27;, &#x27;Total_Lenght&#x27;)</dd><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (time: 1, y: 805, x: 1351)\n",
       "Coordinates:\n",
       "  * y             (y) float64 2.509e+06 2.509e+06 ... 2.501e+06 2.501e+06\n",
       "  * x             (x) float64 7.869e+05 7.869e+05 ... 8.004e+05 8.004e+05\n",
       "  * time          (time) datetime64[ns] 2020-01-01\n",
       "    spatial_ref   int32 0\n",
       "Data variables:\n",
       "    Total_Lenght  (time, y, x) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "Attributes:\n",
       "    transform:      (10.0, 0.0, 786910.0, 0.0, -10.0, 2509270.0)\n",
       "    res:            (10.0, 10.0)\n",
       "    is_tiled:       0\n",
       "    nodatavals:     (nan, nan, nan, nan, nan, nan, nan, nan, nan)\n",
       "    scales:         (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0)\n",
       "    offsets:        (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)\n",
       "    descriptions:   ('Value_SOS', 'doy_SOS', 'value_POS', 'doy_POS', 'value_E...\n",
       "    AREA_OR_POINT:  Area"
      ]
     },
     "execution_count": 609,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "polder_maps_2020"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b21087d6-7718-49c7-a5d2-3687f44d8d6e",
   "metadata": {},
   "source": [
    "# Classify"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 610,
   "id": "2d20a522-1e40-4d69-a521-7923d330dfa6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import joblib\n",
    "import xarray as xr\n",
    "from sklearn.impute import SimpleImputer\n",
    "\n",
    "\n",
    "model_path = joblib.load(r'D:\\crop_season_stats\\results\\model\\model_data_los.joblib')\n",
    "\n",
    "\n",
    "def predict_with_xarray_with_imputation(data):\n",
    "    # Load the pre-trained model from the joblib file\n",
    "    model = model_path.best_estimator_\n",
    "    # Create an imputer object with the chosen strategy\n",
    "    imputer = SimpleImputer(strategy='mean')\n",
    "    # Fit the imputer on the data\n",
    "    imputer.fit(data.values.reshape(-1,1))\n",
    "    # Impute the missing values\n",
    "    data_imputed = imputer.transform(data.values.reshape(-1,1))\n",
    "    # Predict values using the model\n",
    "    predictions = model.predict(data_imputed)\n",
    "    # Create a new xarray DataArray with the predictions\n",
    "    prediction_data = xr.DataArray(predictions.reshape(*data.shape), coords=data.coords, dims=data.dims)\n",
    "    return prediction_data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 611,
   "id": "cbd13dcf-098b-4ed2-be7a-acd4850ea1cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted_16_rice = polder_maps_2016\n",
    "predicted_17_rice = polder_maps_2017\n",
    "predicted_18_rice = polder_maps_2018\n",
    "predicted_19_rice = polder_maps_2019\n",
    "predicted_20_rice = polder_maps_2020\n",
    "predicted_21_rice = polder_maps_2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 612,
   "id": "1342baf5-f5e2-417c-8e97-f189f9d2caf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted_16_rice['Predictions'] = predict_with_xarray_with_imputation(polder_maps_2016.Total_Lenght)\n",
    "predicted_17_rice['Predictions'] = predict_with_xarray_with_imputation(polder_maps_2017.Total_Lenght)\n",
    "predicted_18_rice['Predictions'] = predict_with_xarray_with_imputation(polder_maps_2018.Total_Lenght)\n",
    "predicted_19_rice['Predictions'] = predict_with_xarray_with_imputation(polder_maps_2019.Total_Lenght)\n",
    "predicted_20_rice['Predictions'] = predict_with_xarray_with_imputation(polder_maps_2020.Total_Lenght)\n",
    "predicted_21_rice['Predictions'] = predict_with_xarray_with_imputation(polder_maps_2021.Total_Lenght)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 613,
   "id": "00f0239a-2d50-471b-b5ae-5fc6226bb7e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "rice_type_polder_class_16_pred =  predicted_16_rice.where(mask_class == 0)\n",
    "rice_type_polder_class_17_pred =  predicted_17_rice.where(mask_class == 0)\n",
    "rice_type_polder_class_18_pred =  predicted_18_rice.where(mask_class == 0)\n",
    "rice_type_polder_class_19_pred =  predicted_19_rice.where(mask_class == 0)\n",
    "rice_type_polder_class_20_pred =  predicted_20_rice.where(mask_class == 0)\n",
    "rice_type_polder_class_21_pred =  predicted_21_rice.where(mask_class == 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 614,
   "id": "03c1343f-1edd-4fae-a903-6cb5c90209d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2168b320280>"
      ]
     },
     "execution_count": 614,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rice_type_polder_class_16_pred['Predictions_16'] = rice_type_polder_class_16_pred.Predictions.where(~np.isnan(rice_type_polder_class_16_pred.Predictions), -1)\n",
    "rice_type_polder_class_17_pred['Predictions_17'] = rice_type_polder_class_17_pred.Predictions.where(~np.isnan(rice_type_polder_class_17_pred.Predictions), -1)\n",
    "rice_type_polder_class_18_pred['Predictions_18'] = rice_type_polder_class_18_pred.Predictions.where(~np.isnan(rice_type_polder_class_18_pred.Predictions), -1)\n",
    "rice_type_polder_class_19_pred['Predictions_19'] = rice_type_polder_class_19_pred.Predictions.where(~np.isnan(rice_type_polder_class_19_pred.Predictions), -1)\n",
    "rice_type_polder_class_20_pred['Predictions_20'] = rice_type_polder_class_20_pred.Predictions.where(~np.isnan(rice_type_polder_class_20_pred.Predictions), -1)\n",
    "rice_type_polder_class_21_pred['Predictions_21'] = rice_type_polder_class_21_pred.Predictions.where(~np.isnan(rice_type_polder_class_21_pred.Predictions), -1)\n",
    "rice_type_polder_class_21_pred.Predictions_21.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 615,
   "id": "28b4fc50-a3aa-4976-a7ad-efb946935287",
   "metadata": {},
   "outputs": [],
   "source": [
    "rice_type_polder_class_16_pred.Predictions_16.rio.to_raster(r'D:\\crop_season_stats\\images\\polder_37_4\\maps\\map_class_16.tif',crs='EPSG:32645')\n",
    "rice_type_polder_class_17_pred.Predictions_17.rio.to_raster(r'D:\\crop_season_stats\\images\\polder_37_4\\maps\\map_class_17.tif',crs='EPSG:32645')\n",
    "rice_type_polder_class_18_pred.Predictions_18.rio.to_raster(r'D:\\crop_season_stats\\images\\polder_37_4\\maps\\map_class_18.tif',crs='EPSG:32645')\n",
    "rice_type_polder_class_19_pred.Predictions_19.rio.to_raster(r'D:\\crop_season_stats\\images\\polder_37_4\\maps\\map_class_19.tif',crs='EPSG:32645')\n",
    "rice_type_polder_class_20_pred.Predictions_20.rio.to_raster(r'D:\\crop_season_stats\\images\\polder_37_4\\maps\\map_class_20.tif',crs='EPSG:32645')\n",
    "rice_type_polder_class_21_pred.Predictions_21.rio.to_raster(r'D:\\crop_season_stats\\images\\polder_37_4\\maps\\map_class_21.tif',crs='EPSG:32645')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 616,
   "id": "0879302e-a0db-4ca8-a1c8-0a7ab28141c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "area_calc_16_trad = rice_type_polder_class_16_pred.Predictions_16.where(rice_type_polder_class_16_pred.Predictions_16 == 1).count().values\n",
    "area_calc_16_modern = rice_type_polder_class_16_pred.Predictions_16.where(rice_type_polder_class_16_pred.Predictions_16 == 0).count().values\n",
    "\n",
    "\n",
    "area_calc_17_trad = rice_type_polder_class_17_pred.Predictions_17.where(rice_type_polder_class_17_pred.Predictions_17 == 1).count().values\n",
    "area_calc_17_modern = rice_type_polder_class_17_pred.Predictions_17.where(rice_type_polder_class_17_pred.Predictions_17 == 0).count().values\n",
    "\n",
    "area_calc_18_trad = rice_type_polder_class_18_pred.Predictions_18.where(rice_type_polder_class_18_pred.Predictions_18 == 1).count().values\n",
    "area_calc_18_modern = rice_type_polder_class_18_pred.Predictions_18.where(rice_type_polder_class_18_pred.Predictions_18 == 0).count().values\n",
    "\n",
    "\n",
    "area_calc_19_trad = rice_type_polder_class_19_pred.Predictions_19.where(rice_type_polder_class_19_pred.Predictions_19 == 1).count().values\n",
    "area_calc_19_modern = rice_type_polder_class_19_pred.Predictions_19.where(rice_type_polder_class_19_pred.Predictions_19 == 0).count().values\n",
    "\n",
    "\n",
    "area_calc_20_trad = rice_type_polder_class_20_pred.Predictions_20.where(rice_type_polder_class_20_pred.Predictions_20 == 1).count().values\n",
    "area_calc_20_modern = rice_type_polder_class_20_pred.Predictions_20.where(rice_type_polder_class_20_pred.Predictions_20 == 0).count().values\n",
    "\n",
    "area_calc_21_trad = rice_type_polder_class_21_pred.Predictions_21.where(rice_type_polder_class_21_pred.Predictions_21 == 1).count().values\n",
    "area_calc_21_modern = rice_type_polder_class_21_pred.Predictions_21.where(rice_type_polder_class_21_pred.Predictions_21 == 0).count().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 617,
   "id": "aeec4fd8-86d5-46f3-9311-f0fd96b889be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Traditional</th>\n",
       "      <td>1390.78</td>\n",
       "      <td>1626.77</td>\n",
       "      <td>1413.98</td>\n",
       "      <td>1323.33</td>\n",
       "      <td>1240.55</td>\n",
       "      <td>1237.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Modern</th>\n",
       "      <td>2452.22</td>\n",
       "      <td>2216.23</td>\n",
       "      <td>2429.02</td>\n",
       "      <td>2519.67</td>\n",
       "      <td>2602.45</td>\n",
       "      <td>2605.06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                2016     2017     2018     2019     2020     2021\n",
       "Traditional  1390.78  1626.77  1413.98  1323.33  1240.55  1237.94\n",
       "Modern       2452.22  2216.23  2429.02  2519.67  2602.45  2605.06"
      ]
     },
     "execution_count": 617,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_area_polder_transfer = pd.DataFrame({'2016':[(area_calc_16_trad*100/10000).round(2),(area_calc_16_modern*100/10000).round(2)],\n",
    "                                        \n",
    "                                        '2017':[(area_calc_17_trad*100/10000).round(2),(area_calc_17_modern*100/10000).round(2)],\n",
    "                                        \n",
    "                                        '2018':[(area_calc_18_trad*100/10000).round(2),(area_calc_18_modern*100/10000).round(2)],\n",
    "                                        \n",
    "                                        '2019':[(area_calc_19_trad*100/10000).round(2),(area_calc_19_modern*100/10000).round(2)],\n",
    "                                        \n",
    "                                        '2020':[(area_calc_20_trad*100/10000).round(2),(area_calc_20_modern*100/10000).round(2)],\n",
    "                                        \n",
    "                                        '2021':[(area_calc_21_trad*100/10000).round(2),(area_calc_21_modern*100/10000).round(2)],\n",
    "                                       \n",
    "                                       },\n",
    "                                       \n",
    "                                       index=['Traditional','Modern'])\n",
    "\n",
    "df_area_polder_transfer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 618,
   "id": "d498a61c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Traditional</th>\n",
       "      <td>36.189956</td>\n",
       "      <td>42.330731</td>\n",
       "      <td>36.793651</td>\n",
       "      <td>34.434817</td>\n",
       "      <td>32.28077</td>\n",
       "      <td>32.212855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Modern</th>\n",
       "      <td>63.810044</td>\n",
       "      <td>57.669269</td>\n",
       "      <td>63.206349</td>\n",
       "      <td>65.565183</td>\n",
       "      <td>67.71923</td>\n",
       "      <td>67.787145</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  2016       2017       2018       2019      2020       2021\n",
       "Traditional  36.189956  42.330731  36.793651  34.434817  32.28077  32.212855\n",
       "Modern       63.810044  57.669269  63.206349  65.565183  67.71923  67.787145"
      ]
     },
     "execution_count": 618,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rate_polder_transfer = pd.DataFrame({'2016':[area_calc_16_trad*100/(area_calc_16_trad+area_calc_16_modern),\n",
    "                                                area_calc_16_modern*100/(area_calc_16_trad+area_calc_16_modern)],\n",
    "                                        \n",
    "                                        '2017':[area_calc_17_trad*100/(area_calc_17_trad+area_calc_17_modern),\n",
    "                                                area_calc_17_modern*100/(area_calc_17_trad+area_calc_17_modern)],\n",
    "                                        \n",
    "                                        '2018':[area_calc_18_trad*100/(area_calc_18_trad+area_calc_18_modern),\n",
    "                                                area_calc_18_modern*100/(area_calc_18_trad+area_calc_18_modern)],\n",
    "                                        \n",
    "                                        '2019':[area_calc_19_trad*100/(area_calc_19_trad+area_calc_19_modern),\n",
    "                                                area_calc_19_modern*100/(area_calc_19_trad+area_calc_19_modern)],\n",
    "                                        \n",
    "                                        '2020':[area_calc_20_trad*100/(area_calc_20_trad+area_calc_20_modern),\n",
    "                                                area_calc_20_modern*100/(area_calc_20_trad+area_calc_20_modern)],\n",
    "                                        \n",
    "                                        '2021':[area_calc_21_trad*100/(area_calc_21_trad+area_calc_21_modern),\n",
    "                                                area_calc_21_modern*100/(area_calc_21_trad+area_calc_21_modern)]},  \n",
    "                                       \n",
    "                                 index=['Traditional','Modern'])\n",
    "df_rate_polder_transfer"
   ]
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  {
   "cell_type": "code",
   "execution_count": 619,
   "id": "a1b2e07d-14d1-4c68-9053-ce4fbfabbdb0",
   "metadata": {},
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   "source": [
    "df_area_polder_transfer.to_csv(r'D:\\crop_season_stats\\results\\rate_stats\\polder_37_4_crop_area.csv')\n",
    "df_rate_polder_transfer.to_csv(r'D:\\crop_season_stats\\results\\rate_stats\\polder_37_4_crop_rate.csv')"
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